CrawlLit
An intelligent, multi-threaded web crawler with smart priority scoring for efficient content discovery. CrawlLit uses text-based relevance scoring to prioritize pages based on your search query, making it perfect for targeted web scraping and content discovery
What XERJ indexed
Selected work

Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The owner added it on hub.xerj.org after signing in with GitHub, on 2026-10-29. Same terms as the repository. Answers name the repo, the commit and the file:line.
selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution
The prompt
Paste it into your AI agent. It clones Tuhin-SnapD/CrawlLit at the pinned commit and indexes it on your machine.
Search the GitHub repository Tuhin-SnapD/CrawlLit with XERJ (https://hub.xerj.org/corpus/tuhin-snapd--crawllit). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/Tuhin-SnapD/CrawlLit CrawlLit && git -C CrawlLit checkout 2ffe3e080a62ff5ac07a6e0aef6ca7eecd324dc7 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./CrawlLit --url http://127.0.0.1:9200 --prefix crawllit --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: check the LICENSE file. Keep the copyright notice and credit the authors.
Related
Tuhin ChakrabartyWeb and frontend platform corpora
Stats: GitHub API, fetched 2026-10-29. Selected work and consent: the XERJ registry.